Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/176027
Authors: 
McAleer, Michael
Medeiros, Marcelo C.
Year of Publication: 
2007
Series/Report no.: 
Texto para discussão 544
Abstract: 
In this paper we propose a flexible model to capture nonlinearities and long-range dependence in time series dynamics. The new model is a multiple regime smooth transition extension of the Heterogenous Autoregressive (HAR) model, which is specifically designed to model the behavior of the volatility inherent in financial time series. The model is able to describe simultaneously long memory, as well as sign and size asymmetries. A sequence of tests is developed to determine the number of regimes, and an estimation and testing procedure is presented. Monte Carlo simulations evaluate the finite-sample properties of the proposed tests and estimation procedures. We apply the model to several Dow Jones Industrial Average index stocks using transaction level data from the Trades and Quotes database that covers ten years of data. We find strong support for long memory and both sign and size asymmetries. Furthermore, the new model, when combined with the linear HAR model, is viable and flexible for purposes of forecasting volatility.
Subjects: 
Realized volatility
smooth transition
heterogeneous autoregression
financial econometrics
leverage
sign and size asymmetries
forecasting
risk management
model combination.
Document Type: 
Working Paper
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